Abstract
This paper analyses a local electricity system (LES) comprising photovoltaic production (PV), a connection to the distribution network, local loads and an energy storage system (ESS). Given the flexibility of the ESS, the LES can provide a peak shaving service (PSS) to the grid operator based on the actual monthly power tariff. This paper proposes a stochastic mixed-integer linear programming problem that maximises the expected operating profit of the LES midterm. Assuming a behind customers’ smart meter configuration, income is derived from selling the energy of prosumers to other external electrical areas. If the costs are higher than the income, the net profit will be negative, i.e. a net loss. The cost component of the objective function can be reduced through the management of local resources and by providing PSS to the distribution network operator to minimise the power cost of the monthly power tariff. The model is tested for 720 h (considering a month of 30 days) in three cases: (i) without PV and ESS; (ii) with PV and ESS, where losses are 0%; (iii) with PV and ESS, where losses are 18%. Due to the monthly power tariff, the net loss of the LES is reduced through the optimal management of local resources when the ESS losses are lower than 18%. To assess seasonal implications about the LES, the 12 months of the year are also tested. The month of October indicated the highest peak shaving, while the lowest peak shaving depended on the ESS losses.
Highlights
The electric power grid faces challenges related to the growing share of distributed energy resources (DERs)
This paper demonstrates optimal local electricity management with peak shaving service (PSS), referring to a microgrid-based local market structure specified within the E-REGIO project [1]
The costs associated with the wholesale market (WM) (6) are the wholesale prices plus the grid tariff of the NC multiplied by the energy flow that goes from the NC to the energy storage system (ESS)
Summary
The electric power grid faces challenges related to the growing share of distributed energy resources (DERs (see the table of acronyms Table 1)). The increasing penetration of intermittent power generation boosts the higher deployment of flexibility resources In this respect, local electricity markets (LEMs) strive to provide flexibility-associated benefits for all those connected to local grid parties. To encourage local energy production and active prosumer participation, the local market should offer its participants attractive contracts and have the technology, business and optimisation tools needed to guarantee the fair and efficient utilisation of local resources. In this context, the local electricity system (LES) characteristics (such as grid configuration, types of DERs and local market actors) are important.
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